Multivariate Categorical Relationships

  • A cartoon that can be helpful as a vehicle to discuss how finding a good data visualization to tell the story of a study’s results is an art – even if it must be combined with the science of statistics to give an appropriate impression.  The cartoon was used in the July 2022 CAUSE cartoon caption contest and the winning caption was submitted by John Montagu, a student at University of Colorado, Boulder.. An alternative caption:  "While each plot was from a different perspective, it was the aggregation of the plots that told the whole story." was submitted by Jim Alloway from EMSQ Associates, and reinforces the idea that it may take several graphs to give a full picture of a data set.The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.

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  • A joke relating the voting preferences of certain states with the shape of a map of the states (i.e. the shape they take if viewed as a histogram).  The joke was written in 2019 by Larry Lesser from The University of Texas at El Paso.

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  • A song to be used in discussing the value of visualizations in telling a data story along with the importance of using "clean" data in doing so.   The lyrics were written by Dennis K Pearl from Penn State University in July, 2022.  May be sung to the tune of "Maxwell's Silver Hammer" written by Paul McCartney and released by the Beatles in 1969.

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  • A cartoon suitable for use in teaching about interpreting graphs (e.g. ask: “what does the shaded area in this graph really represent?”). The cartoon is number 2271 (February, 2020) from the webcomic series at xkcd.com created by Randall Munroe. Free to use in the classroom a

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  • A cartoon that can be helpful in introducing time series plots and their interpretation.The cartoon was used in the December 2018 CAUSE cartoon caption contest and the winning caption was written by Greg Baugher from Mercer University, Penfield College. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University.

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  • A cartoon to start a discussion on the importance of appropriate axis labels. The cartoon was used in the September, 2017 CAUSE cartoon caption contest and the winning caption was submitted by Larry Lesser from The University of Texas at El Paso. The cartoon was drawn by British cartoonist John Landers (www.landers.co.uk) based on an idea by Dennis Pearl from Penn State University. Another caption noticed the lack of any scale on the charts read simply "Label your axes!" and was submitted by Kyle Falbo of the College of the Redwoods.  A different use of the cartoon can be made with the caption "Looks like a bad case of Regression to the Mean," which might be used in discussing that topic since the sicker patient in the cartoon is improving more.

     

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  • This paper comes from researchers at the NASA Langley Research Center and College of William & Mary.  

    "The experience of retinex image processing has prompted us to reconsider fundamental aspects of imaging and image processing. Foremost is the idea that a good visual representation requires a non-linear transformation of the recorded (approximately linear) image data. Further, this transformation appears to converge on a specific distribution. Here we investigate the connection between numerical and visual phenomena. Specifically the questions explored are: (1) Is there a well-defined consistent statistical character associated with good visual representations? (2) Does there exist an ideal visual image? And (3) what are its statistical properties?"

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  • The Student Dust Counter is an instrument aboard the NASA New Horizons mission to Pluto, launched in 2006. As it travels to Pluto and beyond, SDC will provide information on the dust that strikes the spacecraft during its 14-year journey across the solar system. These observations will advance human understanding of the origin and evolution of our own solar system, as well as help scientists study planet formation in dust disks around other stars. 

    In this lesson, students learn the concepts of averages, standard deviation from the mean, and error analysis. Students explore the concept of standard deviation from the mean before using the Student Dust Counter data to determine the issues associated with taking data, including error and noise. Questions are deliberately open-ended to encourage exploration.

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  • The Neutral Buoyancy Laboratory allows astronauts an atmosphere resembling zero gravity (weightlessness) in order to train for missions involving spacewalks. In this activity, students will evaluate pressures experienced by astronauts and scuba divers who assist them while training in the NBL.  This lesson addresses correlation, regression, residuals, inerpreting graphs, and making predictions.

    NASA's Math and Science @ Work project provides challenging supplemental problems for students in advanced science, technology, engineering and mathematics, or STEM classes including Physics, Calculus, Biology, Chemistry and Statistics, along with problems for advanced courses in U.S. History and Human Geography.

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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data.  This lecture overs the following: covariance patterns and generalized estimating equations (GEE). 

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